通过循环 R 的条件语句答案

【问题标题】：conditional statements through a loop R通过循环 R 的条件语句
【发布时间】：2019-01-07 15:36:17
【问题描述】：

  unique_ref priority_201801 balance_201801 action_201801 priority_201802 balance_201802 action_201802 priority_201803 balance_201803 action_201803
1          1               3             30   text,letter               1             60        letter               2             30          text
2          2               2            -20         visit               1            -40          text               2            -40          call
3          3               3             35        letter               1             35          call               3            -50          text
4          4               0           -100          call               2              0         visit               2            100          call
  priority_201804 balance_201804 action_201804
1              99              0          text
2               0            -20         visit
3               0            -50        letter
4               0           -100          text

以上是我的数据集示例。我想搜索每个动作，寻找动作“文本”的第一个实例，这将是第 0 周，然后我想排列接下来几周的优先级和余额，如第 1 周、第 2 周等。

理想的输出：

  unique_ref week0_priority week0_balance week0_action week1_priority week1_balance week1_action week2_priority week2_balance week2_action
1          1              3            30         text              1            60       letter              2            30         text
2          2              1           -40         text              2           -40         call              0           -20        visit
3          3              3           -50         text              0           -40       letter        No Data       No Data      No Data
4          4              0          -100         text        No Data       No Data      No Data        No Data       No Data      No Data
  week3_priority week3_balance week3_action
1             99             0         text
2        No Data       No Data      No Data
3        No Data       No Data      No Data
4        No Data       No Data      No Data

可重现的数据示例：

unique_ref=c(1,2,3,4)
priority_201801=c('3','2','3','0')
balance_201801=c('30','-20','35','-100')
action_201801=c('text,letter','visit','letter','call')
priority_201802=c('1','1','1','2')
balance_201802=c('60','-40','35','0')
action_201802=c('letter','text', 'call', 'visit')
priority_201803=c('2','2','3','2')
balance_201803=c('30','-40','-50','100')
action_201803=c('text','call','text','call')
priority_201804=c('99','0','0','0')
balance_201804=c('0','-20','-50','-100')
action_201804=c('text','visit','letter','text')

df3=as.data.frame(cbind(unique_ref,priority_201801,balance_201801,action_201801,priority_201802,balance_201802,action_201802,priority_201803,
                        balance_201803,action_201803,priority_201804,balance_201804,action_201804))

【问题讨论】：

我不太确定你到底想要达到什么目的，但也许尝试将所有信息放在 data.frame 中，因为显然某些信息只是列名的一部分，这是不是正确的数据结构。我认为添加日期列是最简单的。
@hannes101 我有这种格式的数据，我希望它是理想的输出。这就是我问这个问题的原因，这个问题有没有完全不清楚的部分？很高兴澄清任何困惑。
我只是说将其转换为长格式并在修改后恢复为宽格式可能会更容易。

标签： r loops for-loop if-statement

【解决方案1】：

我想出了一个解决方案，涉及对数据进行一些重塑。

library(data.table)
library(tidyr)
library(dplyr)
dt_long <-     gather(data = df3, key = "unique_ref", value = colnames(df3)[2:13])

colnames(dt_long)[2] <- "Values"
dt3_long <- data.table(dt_long)

dt3_long[, c("Type", "Week.Num") := tstrsplit(unique_ref, "_", fixed = TRUE)]


dt3_merge <-  merge(x = dt3_long
      , y =    unique(dt3_long[like(Values, "text"),.(Type
                                                      ,Values
                                                      , Week.Num


      )])[, .(Week.Num, Week.ID = paste0("week", rank(Week.Num, ties.method = "min" )-1))]

      , by.x = "Week.Num"
      , by.y = "Week.Num"
      , all.x = TRUE
      , allow.cartesian = TRUE
      )

生成的 data.table dt3_merge 如下所示，包含所有必要信息，但只需要重新调整即可。

dt3_merge
    Week.Num      unique_ref      Values     Type Week.ID
 1:   201801 priority_201801           3 priority   week0
 2:   201801 priority_201801           2 priority   week0
 3:   201801 priority_201801           3 priority   week0
 4:   201801 priority_201801           0 priority   week0
 5:   201801  balance_201801          30  balance   week0
 6:   201801  balance_201801         -20  balance   week0
 7:   201801  balance_201801          35  balance   week0
 8:   201801  balance_201801        -100  balance   week0
 9:   201801   action_201801 text,letter   action   week0
10:   201801   action_201801       visit   action   week0
11:   201801   action_201801      letter   action   week0
12:   201801   action_201801        call   action   week0
13:   201802 priority_201802           1 priority   week1
14:   201802 priority_201802           1 priority   week1
15:   201802 priority_201802           1 priority   week1
16:   201802 priority_201802           2 priority   week1
17:   201802  balance_201802          60  balance   week1
18:   201802  balance_201802         -40  balance   week1
19:   201802  balance_201802          35  balance   week1
20:   201802  balance_201802           0  balance   week1
21:   201802   action_201802      letter   action   week1
22:   201802   action_201802        text   action   week1
23:   201802   action_201802        call   action   week1
24:   201802   action_201802       visit   action   week1
25:   201803 priority_201803           2 priority   week2
26:   201803 priority_201803           2 priority   week2
27:   201803 priority_201803           3 priority   week2
28:   201803 priority_201803           2 priority   week2
29:   201803  balance_201803          30  balance   week2
30:   201803  balance_201803         -40  balance   week2
31:   201803  balance_201803         -50  balance   week2
32:   201803  balance_201803         100  balance   week2
33:   201803   action_201803        text   action   week2
34:   201803   action_201803        call   action   week2
35:   201803   action_201803        text   action   week2
36:   201803   action_201803        call   action   week2
37:   201804 priority_201804          99 priority   week3
38:   201804 priority_201804           0 priority   week3
39:   201804 priority_201804           0 priority   week3
40:   201804 priority_201804           0 priority   week3
41:   201804  balance_201804           0  balance   week3
42:   201804  balance_201804         -20  balance   week3
43:   201804  balance_201804         -50  balance   week3
44:   201804  balance_201804        -100  balance   week3
45:   201804   action_201804        text   action   week3
46:   201804   action_201804       visit   action   week3
47:   201804   action_201804      letter   action   week3
48:   201804   action_201804        text   action   week3
    Week.Num      unique_ref      Values     Type Week.ID

最后调用 dcast 将其重塑为宽

dt3_merge[, `:=`(id = 1:.N), by = list(unique_ref)]
dt3_result <- dcast(dt3_merge, id ~ Type + Week.ID, value.var=c('Values'))


     id action_week0 action_week1 action_week2 action_week3 balance_week0 balance_week1
1:  1  text,letter       letter         text         text            30            60
2:  2        visit         text         call        visit           -20           -40
3:  3       letter         call         text       letter            35            35
4:  4         call        visit         call         text          -100             0
   balance_week2 balance_week3 priority_week0 priority_week1 priority_week2 priority_week3
1:            30             0              3              1              2             99
2:           -40           -20              2              1              2              0
3:           -50           -50              3              1              3              0
4:           100          -100              0              2              2              0

【讨论】：